DBMS > Google BigQuery vs. Postgres-XL vs. Realm vs. VoltDB

System Properties Comparison Google BigQuery vs. Postgres-XL vs. Realm vs. VoltDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	7.41
Rank	#52	Overall
	#8	Document stores

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

cloud.google.com/bigquery

www.postgres-xl.org

realm.io

www.voltdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.postgres-xl.org/documentation

realm.io/docs

docs.voltdb.com

Developer

Google

Realm, acquired by MongoDB in May 2019

VoltDB Inc.

Initial release

2010

2014

since 2012, originally named StormDB

2014

2010

Current release

10 R1, October 2018

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++

Server operating systems

hosted

Linux
macOS

Android
Backend: server-less
iOS
Windows

Linux
OS X

for development

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Java

with Android only
Objective-C
React Native
Swift

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

runs within the applications so server-side scripts are unnecessary

Java

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

MVCC

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-Memory realm

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

yes

Users and roles with access to stored procedures

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